Analisa Ketangguhan Dan Perubahan Struktur Mikro Patahan Akibat Heat Treatment Dan Variasi Sudut Impact Pada Baja ST 60

Tujuan dalam penelitian ini adalah untuk menganalisa: (1) Ketangguhan baja St 60 akibat heat treatment dengan suhu 600 °C dan dengan variasi sudut α = 90° dan α = 120°. (2) Ketangguhan baja St 60 akibat heat treatment dengan suhu 900 °C dan dengan variasi sudut α = 90° dan α = 120°. (3) Bentuk patahan baja St 60 setelah mengalami perlakuan panas dan uji ketangguhan dengan variasi sudut α = 90° dan α = 120°. Desain penelitiannya adalah penelitian eksperimental yang dilakukan di laboratorium. Teknik analisis data menggunakan analisis deskriptif. Hasil penelitian adalah baja St 60 setelah dipanaskan, ketangguhan baja akan meningkat. Serta pada struktur mikro patahan baja St 60 terjadi fenomena ductile to brittle transition, salah satu penyebab fenomena ini adalah laju regangan tinggi. awalnya merupakan material ulet tetapi mengalami patah getas. Transisinya juga bisa diamati dari permukaan patahan, akan tampak serabut-serabut pada patahan yang benar-benar bersifat ulet, dan tampak butiran-butiran kecil yang terlihat mengkilap pada patahan yang benar-benar bersifat getas

Clones in Graphs

Finding structural similarities in graph data, like social networks, is a far-ranging task in data mining and knowledge discovery. A (conceptually) simple reduction would be to compute the automorphism group of a graph. However, this approach is ineffective in data mining since real world data does not exhibit enough structural regularity. Here we step in with a novel approach based on mappings that preserve the maximal cliques. For this we exploit the well known correspondence between bipartite graphs and the data structure formal context $(G,M,I)$ from Formal Concept Analysis. From there we utilize the notion of clone items. The investigation of these is still an open problem to which we add new insights with this work. Furthermore, we produce a substantial experimental investigation of real world data. We conclude with demonstrating the generalization of clone items to permutations.Comment: 11 pages, 2 figures, 1 tabl

Severity of Visual Field Loss at First Presentation to Glaucoma Clinics in England and Tanzania

Purpose: To compare severity of visual field (VF) loss at first presentation in glaucoma clinics in England and Tanzania. Methods: Large archives of VF records from automated perimetry were used to retrospectively examine vision loss at first presentation in glaucoma clinics in Tanzania (N = 1,502) and England (N = 9,264). Mean deviation (MD) of the worse eye at the first hospital visit was used as an estimate of detectable VF loss severity. Results: In Tanzania, 44.7% {CI95%: 42.2, 47.2} of patients presented with severe VF loss (< −20 dB), versus 4.6% {4.1, 5.0} in England. If we consider late presentation to also include cases of advanced loss (-12.01 dB to -20 dB), then the proportion of patients presenting late was 58.1% {55.6, 60.6} and 14.0% {13.3, 14.7}, respectively. The proportion of late presentations was greater in Tanzania at all ages, but the difference was particularly pronounced among working-age adults, with 50.3% {46.9, 53.7} of 18–65-year-olds presenting with advanced or severe VF loss, versus 10.2% {9.3, 11.3} in England. In both countries, men were more likely to present late than women. Conclusions: Late presentation of glaucoma is a problem in England, and an even greater challenge in Tanzania. Possible solutions are discussed, including increased community eye-care, and a more proactive approach to case finding through the use of disruptive new technologies, such as low-cost, portable diagnostic aids

Ordinary-derivative formulation of conformal totally symmetric arbitrary spin bosonic fields

Conformal totally symmetric arbitrary spin bosonic fields in flat space-time of even dimension greater than or equal to four are studied. Second-derivative (ordinary-derivative) formulation for such fields is developed. We obtain gauge invariant Lagrangian and the corresponding gauge transformations. Gauge symmetries are realized by involving the Stueckelberg and auxiliary fields. Realization of global conformal boost symmetries on conformal gauge fields is obtained. Modified de Donder gauge condition and de Donder-Stueckelberg gauge condition are introduced. Using the de Donder-Stueckelberg gauge frame, equivalence of the ordinary-derivative and higher-derivative approaches is demonstrated. On-shell degrees of freedom of the arbitrary spin conformal field are analyzed. Ordinary-derivative light-cone gauge Lagrangian of conformal fields is also presented. Interrelations between the ordinary-derivative gauge invariant formulation of conformal fields and the gauge invariant formulation of massive fields are discussed.Comment: 51 pages, v2: Results and conclusions of v1 unchanged. In Sec.3, brief review of higher-derivative approaches added. In Sec.4, new representations for Lagrangian, modified de Donder gauge, and de Donder-Stueckelberg gauge added. In Sec.5, discussion of interrelations between the ordinary-derivative and higher-derivative approaches added. Appendices A,B,C,D and references adde

Statistical relational learning with soft quantifiers

Quantification in statistical relational learning (SRL) is either existential or universal, however humans might be more inclined to express knowledge using soft quantifiers, such as ``most'' and ``a few''. In this paper, we define the syntax and semantics of PSL^Q, a new SRL framework that supports reasoning with soft quantifiers, and present its most probable explanation (MPE) inference algorithm. To the best of our knowledge, PSL^Q is the first SRL framework that combines soft quantifiers with first-order logic rules for modelling uncertain relational data. Our experimental results for link prediction in social trust networks demonstrate that the use of soft quantifiers not only allows for a natural and intuitive formulation of domain knowledge, but also improves the accuracy of inferred results

A life cycle stakeholder management framework for enhanced collaboration between stakeholders with competing interests

This is a postprint version of the Book Chapter. Information regarding the official publication is available from the link below - Copyright @ 2011 SpringerImplementation of a Life Cycle Sustainability Management (LCSM) strategy can involve significant challenges because of competing or conflicting objectives between stakeholders. These differences may, if not identified and managed, hinder successful adoption of sustainability initiatives. This article proposes a conceptual framework for stakeholder management in a LCSM context. The framework identifies the key sustainability stakeholder groups and suggests strategic ambiguity as a management tool to harness dysfunctional conflict into constructive collaboration. The framework is of practical value as it can be used as a guideline by managers who wish to improve collaboration with stakeholders along the supply chain. The article also fills a gap in the academic literature where there is only limited research on sustainability stakeholder management through strategic ambiguity

Survivin a radiogenetic promoter for glioblastoma viral gene therapy independently from CArG motifs

BACKGROUND: Radiogenetic therapy is a novel approach in the treatment of cancer, which employs genetic modification to alter the sensitivity of tumor cells to the effect of applied radiation. AIM: To select a potent radiation inducible promoter in the context of brain tumors and to investigate if CArG radio responsive motifs or other elements in the promoter nucleotide sequences can correlate to its response to radiation. METHODS: To select initial candidates for promoter inducible elements, the levels of mRNA expression of six different promoters were assessed using Quantitative RTPCR in D54 MG cells before and after radiation exposure. Recombinant Ad/reporter genes driven by five different promoters; CMV, VEGF, FLT-1, DR5 and survivin were constructed. Glioma cell lines were infected with different multiplicity of infection of the (promoter) Ad or CMV Ad. Cells were then exposed to a range of radiation (0–12 Gy) at single fraction. Fluorescent microscopy, Luc assay and X-gal staining was used to detect the level of expression of related genes. Different glioma cell lines and normal astrocytes were infected with Ad survivin and exposed to radiation. The promoters were analyzed for presence of CArG radio-responsive motifs and CCAAT box consensus using NCBI blast bioinformatics software. RESULTS: Radiotherapy increases the expression of gene expression by 1.25–2.5 fold in different promoters other than survivin after 2 h of radiation. RNA analysis was done and has shown an increase in copy number of tenfold for survivin. Most importantly cells treated with RT and Ad Luc driven by survivin promoter showed a fivefold increase in expression after 2 Gy of radiation in comparison to non-irradiated cells. Presence or absence of CArG motifs did not correlate with promoter response to radiation. Survivin with the best response to radiation had the lowest number of CCAAT box. CONCLUSION: Survivin is a selective potent radiation inducible promoter for glioblastoma viral gene therapy and this response to radiation could be independent of CArG motifs

Harmonic Analysis of Boolean Networks: Determinative Power and Perturbations

Consider a large Boolean network with a feed forward structure. Given a probability distribution on the inputs, can one find, possibly small, collections of input nodes that determine the states of most other nodes in the network? To answer this question, a notion that quantifies the determinative power of an input over the states of the nodes in the network is needed. We argue that the mutual information (MI) between a given subset of the inputs X = {X_1, ..., X_n} of some node i and its associated function f_i(X) quantifies the determinative power of this set of inputs over node i. We compare the determinative power of a set of inputs to the sensitivity to perturbations to these inputs, and find that, maybe surprisingly, an input that has large sensitivity to perturbations does not necessarily have large determinative power. However, for unate functions, which play an important role in genetic regulatory networks, we find a direct relation between MI and sensitivity to perturbations. As an application of our results, we analyze the large-scale regulatory network of Escherichia coli. We identify the most determinative nodes and show that a small subset of those reduces the overall uncertainty of the network state significantly. Furthermore, the network is found to be tolerant to perturbations of its inputs

Geometry dominated fluid adsorption on sculptured substrates

Experimental methods allow the shape and chemical composition of solid surfaces to be controlled at a mesoscopic level. Exposing such structured substrates to a gas close to coexistence with its liquid can produce quite distinct adsorption characteristics compared to that occuring for planar systems, which may well play an important role in developing technologies such as super-repellent surfaces or micro-fluidics. Recent studies have concentrated on adsorption of liquids at rough and heterogeneous substrates and the characterisation of nanoscopic liquid films. However, the fundamental effect of geometry has hardly been addressed. Here we show that varying the shape of the substrate can exert a profound influence on the adsorption isotherms allowing us to smoothly connect wetting and capillary condensation through a number of novel and distinct examples of fluid interfacial phenomena. This opens the possibility of tailoring the adsorption properties of solid substrates by sculpturing their surface shape.Comment: 6 pages, 4 figure

Semantic distillation: a method for clustering objects by their contextual specificity

Techniques for data-mining, latent semantic analysis, contextual search of databases, etc. have long ago been developed by computer scientists working on information retrieval (IR). Experimental scientists, from all disciplines, having to analyse large collections of raw experimental data (astronomical, physical, biological, etc.) have developed powerful methods for their statistical analysis and for clustering, categorising, and classifying objects. Finally, physicists have developed a theory of quantum measurement, unifying the logical, algebraic, and probabilistic aspects of queries into a single formalism. The purpose of this paper is twofold: first to show that when formulated at an abstract level, problems from IR, from statistical data analysis, and from physical measurement theories are very similar and hence can profitably be cross-fertilised, and, secondly, to propose a novel method of fuzzy hierarchical clustering, termed \textit{semantic distillation} -- strongly inspired from the theory of quantum measurement --, we developed to analyse raw data coming from various types of experiments on DNA arrays. We illustrate the method by analysing DNA arrays experiments and clustering the genes of the array according to their specificity.Comment: Accepted for publication in Studies in Computational Intelligence, Springer-Verla